Feature and Contrast Enhancement of Mammographic Image Based on Multiscale Analysis and Morphology

被引：6

作者：

Wu, Shibin ^{[1
,2
]}

Yu, Shaode ^{[1
,2
]}

Yang, Yuhan ^{[1
,2
]}

Xie, Yaoqin ^{[1
,2
]}

机构：

[1] Chinese Acad Sci, Shenzhen Inst Adv Technol, Beijing 100864, Peoples R China

[2] Shenzhen Key Lab Low Cost Healthcare, Shenzhen, Peoples R China

来源：

COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE | 2013年 / 2013卷

基金：

中国国家自然科学基金;

关键词：

23;

D O I：

10.1155/2013/716948

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

A new algorithm for feature and contrast enhancement of mammographic images is proposed in this paper. The approach bases on multiscale transform and mathematical morphology. First of all, the Laplacian Gaussian pyramid operator is applied to transform the mammography into different scale subband images. In addition, the detail or high frequency subimages are equalized by contrast limited adaptive histogram equalization (CLAHE) and low-pass subimages are processed by mathematical morphology. Finally, the enhanced image of feature and contrast is reconstructed from the Laplacian Gaussian pyramid coefficients modified at one or more levels by contrast limited adaptive histogram equalization and mathematical morphology, respectively. The enhanced image is processed by global nonlinear operator. The experimental results show that the presented algorithm is effective for feature and contrast enhancement of mammogram. The performance evaluation of the proposed algorithm is measured by contrast evaluation criterion for image, signal-noise-ratio (SNR), and contrast improvement index (CII).

引用

页数：8